Online Comments Affecting Consumer Network Group Buy On Factors

Since the spring of 2010, group purchase has passed more than three years at home, which has gone through the rise, inflation, white-hot competition until the doubled stationary phase followed the number fall after rise again. In China, group purchase has also become comprehensive from a single group to the e-commerce sites within the group purchase channel and new formats of composite trading platform. According to the data from Group 800, group-buying market turnover is 35.88 billion at 2013, which increase 67.7% compared to 2012, the net gaining is 14.49 billion. On selling lists are 5.715 million, increase 128.7% compared to 2012, the net gaining is 3.216 million.After two years’ ‘crazy’ between 2010 and 2011, and ‘panic’ in 2012, group purchase has become much more popular, meanwhile it also let consumers become more rational when facing it. Price is no longer the only focus, group-buying consumers also consider other factors when comparing the price, such as the group reliability, list qualities, comments, etc. Among which the online group-buying comments have played a very important role in guiding consumers’ willingness. Therefore, the study on the influence factors of online comments on consumer purchase seems necessaryAt present, scholars at home and abroad for online comments and network group purchase have a lot of researches, but not combine them organically. With the gradually mature of network group purchase, the influence of online comments on it has become more and more important, therefore, this article treats the dianping.com as the research object, using the data mining technology to collect the local group purchases of service class whose food service is the most representative. Studying the influence of list discount, merchants’ star levels, business average scores and the number of online comments on group purchase’ sales volume. The results show that the list discount, average scores and the number of online comments have significant impacts the sales volume, while merchants’ star levels, comments’ length have less influence. Finally, according to the results, this article is trying to take some managerial implications to groupwebsites and merchants.